GPU clusters, HPC environments, and AI-ready infrastructure stacks on NVIDIA and AMD silicon. From training to inference to edge — we design, deploy, and support it all.
Multi-node GPU clusters configured for deep learning training workloads. NVIDIA A100, H100, and L40S with high-bandwidth interconnects, optimized networking, and liquid/air cooling solutions.
Compute-dense environments for simulation, modeling, and scientific workloads. AMD EPYC and Intel Xeon processors paired with GPU accelerators for maximum throughput.
Low-latency inference stacks deployed at the edge for real-time decision-making. Compact, ruggedized hardware for manufacturing floors, retail, healthcare, and field operations.
High-bandwidth, low-latency networking (InfiniBand, RoCE) and parallel file systems designed for the I/O demands of AI training pipelines and large model checkpointing.
Ongoing management, monitoring, and optimization of your AI compute environment. Certified engineers handling firmware, driver updates, cluster health, and capacity planning.
Purpose-built AI data center environments: power planning, cooling design, rack layout, cabling, and commissioning for GPU-dense installations.
A100 • H100 • L40S • Grace Hopper
Instinct MI300X • EPYC Processors
Xeon Scalable • Gaudi Accelerators
PowerEdge XE Series for AI
Cray EX • ProLiant DL380a
ThinkSystem SR670 V2 for AI
Understand your AI workload requirements, data pipeline, and performance targets.
Architect the compute, networking, storage, and cooling stack tailored to your workloads.
Procure, rack, cable, configure, and commission. Production-ready, not just delivered.
Ongoing monitoring, optimization, firmware management, and capacity planning.
Our solutions architects can design a compute stack tailored to your training, inference, and deployment needs.
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